Using machine translation to support ESL pre-service teachers’ collaborative feedback for writing

Date
2024-04-15
Authors
Fu, Linling
Gu, Michelle Mingyue
Jin, Tan
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University of Hawaii National Foreign Language Resource Center
Center for Language & Technology
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28
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1
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1
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13
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Abstract
The application of machine translation (MT) in ESL (English as a Second Language) writing has thrived over the past decade. However, how MT impacts pre-service teachers’ (PSTs) provision of collaborative feedback for writing remains an under-explored domain. Such knowledge will facilitate pre-service teacher education to be more scientific and practical. In this study, we investigated the effects of MT in assisting PSTs’ provision of feedback, drawing on six PSTs’ in-class discussions and the results of their revision. Additionally, we conducted interviews to learn their perception of MT. The findings revealed that MT assisted them in providing feedback on students’ L2 writing, especially in improving content, communicative achievement, and language issues. PSTs in the study held positive attitudes towards using MT in their collaborative revision for writing. The findings also suggest that applying MT to ESL pre-service teacher education is beneficial, especially in assisting their writing revision. It is also advisable to utilise MT with other tools. The implications of the findings are discussed.
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Keywords
Machine Translation, Collaborative Feedback, Writing Correction, Pre-Service Teachers
Citation
Fu, L., Gu, M., & Jin, T. (2024). Using machine translation to support ESL pre-service teachers’ collaborative feedback for writing. Language Learning & Technology, 28(1), 1–13. https://hdl.handle.net/10125/73557
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13
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